US10274565B2 - Magnetic resonance imaging - Google Patents

Magnetic resonance imaging Download PDF

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US10274565B2
US10274565B2 US14/726,375 US201514726375A US10274565B2 US 10274565 B2 US10274565 B2 US 10274565B2 US 201514726375 A US201514726375 A US 201514726375A US 10274565 B2 US10274565 B2 US 10274565B2
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phase
fat
chemical species
signal
peak
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US20150285883A1 (en
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Paul Clark
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MAGNEPATH Pty Ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R33/00—Arrangements or instruments for measuring magnetic variables
    • G01R33/20—Arrangements or instruments for measuring magnetic variables involving magnetic resonance
    • G01R33/44—Arrangements or instruments for measuring magnetic variables involving magnetic resonance using nuclear magnetic resonance [NMR]
    • G01R33/48—NMR imaging systems
    • G01R33/4828—Resolving the MR signals of different chemical species, e.g. water-fat imaging
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves
    • A61B5/055—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R33/00—Arrangements or instruments for measuring magnetic variables
    • G01R33/20—Arrangements or instruments for measuring magnetic variables involving magnetic resonance
    • G01R33/44—Arrangements or instruments for measuring magnetic variables involving magnetic resonance using nuclear magnetic resonance [NMR]
    • G01R33/48—NMR imaging systems
    • G01R33/54—Signal processing systems, e.g. using pulse sequences ; Generation or control of pulse sequences; Operator console
    • G01R33/56—Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution
    • G01R33/561—Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution by reduction of the scanning time, i.e. fast acquiring systems, e.g. using echo-planar pulse sequences
    • G01R33/5615—Echo train techniques involving acquiring plural, differently encoded, echo signals after one RF excitation, e.g. using gradient refocusing in echo planar imaging [EPI], RF refocusing in rapid acquisition with relaxation enhancement [RARE] or using both RF and gradient refocusing in gradient and spin echo imaging [GRASE]
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R33/00—Arrangements or instruments for measuring magnetic variables
    • G01R33/20—Arrangements or instruments for measuring magnetic variables involving magnetic resonance
    • G01R33/44—Arrangements or instruments for measuring magnetic variables involving magnetic resonance using nuclear magnetic resonance [NMR]
    • G01R33/48—NMR imaging systems
    • G01R33/58—Calibration of imaging systems, e.g. using test probes, Phantoms; Calibration objects or fiducial markers such as active or passive RF coils surrounding an MR active material
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/48—Other medical applications
    • A61B5/4869—Determining body composition

Definitions

  • the present invention relates to magnetic resonance imaging.
  • MR imaging techniques typically detect a signal from hydrogen protons.
  • the detected hydrogen protons are predominantly part of water, or part of organic molecules such as proteins, carbohydrates, and fat, or part of introduced inorganic-organic complexes, such as silicone.
  • the respective signal intensities of the various hydrogen proton pools in an imaging voxel results from a combination of their spin density, longitudinal and transverse, relaxation time (T 1 and T 2 , respectively), and the parameters of the imaging sequence used.
  • MR imaging provides good contrast between soft tissues, according to the chemical form and local microscopic environment of the hydrogen containing species in the tissues, such as silicone or lipid (fat) molecules.
  • the electronic shielding of the hydrogen protons in macromolecules such as fat or silicone is greater than that experienced by hydrogen protons in water. This results in different microscopic magnetic field environments for the hydrogen protons, and subsequently different hydrogen proton resonant frequencies for the different hydrogen-containing chemical species—referred to as chemical shift.
  • fat is known to have a complex spectrum with multiple peaks owing to its various hydrogen proton chains, for which the largest peak is shifted downfield by ⁇ 3.5 ppm from the peak for water.
  • a known MR imaging modality relies on suppression of the fat peak compared to the water peak.
  • a more advanced approach for fat suppression relative to the water peak is to excite the water peak directly via spatial spectral pulses, rather than suppress the fat peak.
  • NAFLD non-alcoholic fatty liver disease
  • liver biopsy which is expensive, risky, and suffers from high sampling variability, greatly limiting its clinical utility. Therefore, there is a great need for noninvasive biomarkers such as imaging, not only for early detection of disease, but also to reliably quantify the severity of disease.
  • the water/fat ambiguity problem that arises in the fitting of a bi-exponential signal decay model to gradient-echo image data arises from over-simplification of the model where fat is characterised by a single resonant frequency.
  • the ambiguity has the potential for being resolved by using a multi-peak spectral model for fat instead that accounts for contributions to the MR signal from the major hydrogen proton groups on the fat molecule, but utility beyond the 50% fat fraction has not been demonstrated by magnitude-based techniques employing this approach (Yokoo et al in 2011).
  • an aspect of the present invention provides a method of characterizing relative proportions of magnetic resonance (MR) chemical species where one or more of the chemical species has a multi-peak MR spectra, the method including:
  • the method may be expanded to including identifying deviation in signal over the out-phase window relative to the reference signal decay over the out-phase window, where such out-phase deviation acts as an indicator of the reduced presence of the one or more multi-peak spectral species relative to the other species.
  • One or more forms of the present invention advantageously enables MR imaging of the multi peak chemical species.
  • the multi peak chemical species is fat or silicone.
  • the proportion and distribution of fat in a body such as visceral and/or sub-cutaneous fat, or within an organ or tissue, such as the liver, may be MR imaged using one or more embodiments of the present invention.
  • the reference signal decay may be taken to be representative of averaging the relaxation affects of the chemical species contributing to the MR signal, such that it may be further represented by a single exponential decay.
  • One or more embodiments of the present invention beneficially enables the characterization of magnetic resonance (MR) relaxation rates and relative proportions of two different magnetic resonant chemical species, where one chemical species has two or more dominant MR spectral peaks (such as the 1H MR spectra of fat) relative to the other chemical species that has one dominant MR spectral peak (such as for the 1H MR spectra of water).
  • MR magnetic resonance
  • the present invention advantageously enables imaging of the percentage/proportion amount of fat (or other selected species) and water in tissues.
  • the present invention can be employed to identify other multi-spectral species relative to water.
  • silicone to identify and quantify the leakage of silicone from implants into or adjacent tissues.
  • the present invention overcomes the problem of mis-assigning and/or sufficiently refining the initial estimates of the fat and water components through analysis of the behaviour between two peaks of a multi-peak spectral model for the target chemical species, such as fat, with respect to the single (water) resonant peak.
  • the estimate of the percentage fat fraction can be further refined to take into account other potential confounds, such as R2* enhancement, the extent of which can also be estimated from the echo time image data collected.
  • a further embodiment of the present invention includes determining reference signal decay by an empirical approach including the steps of: fractioning the out-phase window into two smaller windows, determining an average intensity value and an average measurement time value in each of the smaller windows, and using the two average intensity/measurement time pairs to determine a 2-point approximation for the reference relaxation process according to the equation of single exponential decay.
  • the deviation in signal intensity may be determined from the reference signal decay by subtracting the reference signal intensity calculated from the reference relaxation equation at a given measurement time from the actual signal intensity at that measurement time, normalised relative to that actual signal intensity.
  • Characteristic in-phase or out-phase deviation may be determined from the in-phase or out-phase deviations, respectively.
  • a characteristic in-phase or out-phase deviation may be determined as the greatest absolute deviation over the in-phase or out-phase window, respectively.
  • a method of the present invention may include determining the proportion of a multi-peak chemical species by a combination of scaling and thresholding of the in-phase and out-phase deviations.
  • a lesser proportion of the multi-peak chemical species relative to the other species may be taken to be equal to the scaled out-phase deviation within empirically determined thresholds for the in-phase and out-phase deviations.
  • a greater proportion of the multi-peak chemical species relative to the other species may be taken to be equal to a scaling of one minus the scaled out-phase deviation outside of empirically determined thresholds for the in-phase and out-phase deviations.
  • One or more embodiments of the present invention may use the proportion of the multi-peak chemical species to determine initial estimates of the signal intensities of the chemical species at a zero measurement time with reference to the signal intensity at a zero measurement time from the reference signal decay.
  • one or more embodiments of the present invention includes characterizing magnetic resonance (MR) relaxation rates and relative proportions of the two or more magnetic resonant chemical species, where one said chemical species has two or more dominant MR spectral peaks relative to the other said chemical species that has one dominant MR spectral peak.
  • MR magnetic resonance
  • One or more embodiments of the present invention may include characterizing magnetic resonance (MR) relaxation rates and relative proportions of the two or more magnetic resonant chemical species, where one said chemical species has two or more dominant MR spectral peaks relative to the other said chemical species that has one dominant MR spectral peak.
  • MR magnetic resonance
  • the chemical species with two or more dominant spectral peaks is fat and the chemical species with one dominant spectral peak is water.
  • a percentage or proportion of fat fraction may be estimated, preferably including accounting for one or more additional confounds from collected echo time image data.
  • One or more additional confounds may include R2* enhancement.
  • gradient-echo image data may be collected out to echo times where either complex signals from the two chemical species are next in-phase after having first been out of phase, or to where complex signals for two dominant hydrogen proton pools of the species with a multi-peak spectra are next in phase having been first out of phase, whichever is the longer.
  • the relative proportions of the two or more chemical species may be estimated by separating collected data out to the longest echo time into two measurement time windows.
  • a first measurement time window may extend out from an echo time of 0 ms to an echo time point where the complex signals from the two dominant fat hydrogen proton pools are first out of phase.
  • a second measurement time window may cover a span of echo times where the complex signal from the two dominant fat hydrogen proton pools are coming back in phase.
  • FIG. 1 shows a graph of magnetic resonance (MR) spectra (spectral diagram) revealing the separation in peaks for water and fat.
  • FIG. 2 shows a gradient echo decay indicating the in-phase and out-phase oscillation for water and fat.
  • FIG. 3 shows specific in-phase and out-phase windows from the gradient echo decay trace of FIG. 2 .
  • FIG. 4 a shows a graph of an initial estimate of presence of fat in phantoms from an actual test of the present invention
  • FIG. 4 b shows a graph of fitted results using the initial estimates.
  • FIGS. 5 a and 5 b show percentage fat maps on phantoms imaged at 3.0 T within circular regions of interest, of the initial estimates realized by employing an embodiment of the present invention ( FIG. 5 b ) and from fitted results using the initial estimates ( FIG. 5 a ), respectively.
  • FIG. 6 a shows an image of phantoms containing fat and imaged utilizing an embodiment of the present invention.
  • FIG. 6 b shows a graph of Region Average % fat to Actual fat % with the % fat realized from the phantoms on an expected 1-to-1 line.
  • FIG. 7 shows a spectral diagram revealing the separation in peaks between water and silicone.
  • a fat MR spectrum is shown with multiple peaks 1 - 6 , with the dominant (fat 1 ) peak separated 3.4 ppm from a dominant water peak.
  • the fat 2 secondary peak is separated 0.8 ppm from the dominant fat 1 peak.
  • a gradient echo decay graph is shown in FIG. 2 for a field strength of 1.5 T.
  • a decay line shows as a sinusoidal oscillation between water and fat in-phase maxima and water and fat out-phase minima.
  • the dominant fat 1 and secondary fat 2 in-phase maximum is shown at 19.6 ms, and the out-phase minimum at 9.8 ms.
  • FIG. 3 identifies the respective out-phase and in-phase windows.
  • magnitude gradient echo image data was acquired on phantoms and volunteers at 1.5 T and 3.0 T (Siemens Avanto and Philips Achieva, respectively), with a maximum scan time of 30 s.
  • Test phantoms included yogurt, cream, butter, lard, and sausages, for which the percentage fat content was obtained from the nutritional information on the product labels.
  • a 2-D multi-echo spoiled gradient echo sequence was run with the following parameters: flip angle 20° and TR 200 ms to reduce T1-weighting; 8 equally spaced echo times per field strength of 3.6 ms.T, slice thickness 8 mm; bandwidth of 500 Hz/pixel (at 1.5 T) and 1970 Hz/pixel (at 3.0 T); matrix size 256 pixels.
  • a magnitude-based gradient echo image technique for 0 to 100% fat-water separation with dual R2* mapping was conducted.
  • a multi-peak spectral model for fat was implemented with five frequency components of 243 Hz, 217 Hz, 166 Hz, 32 Hz, and ⁇ 38 Hz (per 1.5 T) relative to water, with corresponding normalised weights of 0.09, 0.7, 0.12, 0.04, and 0.05, as reported in the literature.
  • Separate R2* parameters were modelled for water and fat.
  • Non-linear curve fitting was performed pixel-by-pixel to signal power as a function of echo time using a simplex simulated annealing technique.
  • the non-zero baseline of the magnitude image data was subtracted in quadrature from the pixel signal intensities prior to fitting.
  • Initial estimates for the fat and water signal proportions were calculated from an embodiment of this invention.
  • the fitted signal fractions were converted to volume fractions to provide percentage fat concentrations. Accuracy and precision were calculated as the mean and standard deviation of the differences between the calculated and labelled fat concentrations.
  • FIG. 4 a gives an example as a graph of an initial estimate of % of fat compared to actual % fat.
  • FIG. 4 b is an example of a fitted result of % of fat compared to actual % fat.
  • FIG. 4 b shows average fat percentages for each phantom region of interest plotted versus the labelled fat concentrations on the products.
  • the embodiment of the present invention the basis for the results in FIG. 4 b was accurate to within 0.2%, and precise to within 2.5%.
  • FIGS. 5 a and 5 b show percentage fat maps on phantoms imaged at 3.0 T within circular regions of interest, of the initial estimates realized by employing an embodiment of the present invention and front fitted results using the initial estimates, respectively.
  • One or more embodiments of the present invention enables estimation of the relative proportions of two dominant MR chemical species from magnitude gradient-echo image data, where one species has a multi-peak MR spectra that has two dominant peaks.
  • MR signal volume comprising water and fat
  • present invention can be applied to other MR chemical species, such as silicone.
  • a silicone MR spectrum is shown with multiple peaks 1 - 3 , with the dominant (silicone 1 ) peak separated ⁇ 5.0 ppm from a dominant water peak.
  • the silicone 2 secondary peak is separated ⁇ 0.6 ppm from the dominant silicone 1 peak. (A residual fat peak is left after near-total suppression of the fat signal).
  • the same pulse sequence can be used—a 2D spoiled gradient echo pulse sequence—in respect of silicone as for fat, but with the additional requirement that the images be acquired with fat suppression.
  • magnitude gradient echo image data can be acquired on phantoms and volunteers at 1.5 T and 3.0 T (Siemens Avanto and Philips Achieva, respectively) for silicone.
  • a maximum scan time of 30 s can be used.
  • a 2-D multi-echo spoiled gradient echo sequence (with fat suppression) is proposed with the following parameters: flip angle 20° and TR 200 ms to reduce T1-weighting; 16 equally spaced echo times per field strength of ⁇ 1.0 ms.T, slice thickness 8 mm; bandwidth of 500 Hz/pixel (at 1.5 T) and 1970 Hz/pixel (at 3.0 T); matrix size 256 pixels.
  • the amount of data collected out to the outer echo time for magnitude fitting of a combined silicone/water signal model should be in increments where the silicone and water signal go approximately in and out of phase, at half of 3.1 ms, which is every 1.55 ms at 1.5 T, such that up to 16 separate echo time images are collected out to 24.8 ms, or up to 12 echo time images are collected out to 18.6 ms (75% of 24.8 ms).
  • the fat signals can be suppressed so that the silicone signal is revealed as a bright image.
  • Gradient-echo image data is required to be collected out to echo times in the vicinity where either the complex signals from the two MR species are next in-phase after having first been out of phase, or to where the complex signals for the two dominant hydrogen proton pools of the species with a multi-peak spectra are next in phase having been first out of phase, whichever is the longer.
  • the amount of data collected out to the outer echo time for magnitude fitting of a combined fat/water signal model should be in increments where the fat and water signal go approximately in and out of phase, at half of 4.8 ms, which is every 2.4 ms at 1.5 T, such that up to 8 separate echo time images are collected out to 19.6 ms, or up to 6 echo time images are collected out to 14.7 ms (75% of 19.6 ms).
  • the first measurement time window extends out from an echo time of 0 ms to the echo time point where the complex signals from the two dominant fat hydrogen proton pools are first out of phase, which is at half the echo time from where they are next in phase.
  • the end point for the first measurement time window is then in the vicinity of half of 19.6 ms, at ⁇ 9.8 ms.
  • the second measurement time window covers a span of echo times where the complex signal from the two dominant fat hydrogen proton pools are coming back in phase. This can be from the point at 9.8 ms out to 19.6 ms, or overlapping with the first window, from down to ⁇ 75% of these values, from ⁇ 7.3 ms out to ⁇ 14.7 ms.
  • the first measurement time window thus captures signal data up to where the two dominant hydrogen proton pools for fat go maximally out of phase (the “out-phase window”), whilst the second measurement time windows captures data where the complex signals from the two dominant hydrogen proton pools are coming back in phase (the “in-phase window”).
  • the out-phase and in-phase windows should thus span four different echo time images.
  • the reference relaxation process is taken to be the average relaxation process for all hydrogen protons, described by a single exponential decay, although other signal model decay representations could be used.
  • the reference relaxation process can modelled from the data by either curve fitting or other means of approximation, which may include empirical ones.
  • Deviation in signal intensities relative to the reference relaxation process may be calculated in a number of ways. However, a preferred method is to subtract the reference signal intensity calculated from the reference relaxation equation at a given echo time from the actual signal intensity at that echo time, normalized relative to that actual signal intensity.
  • a list of deviations is thus obtained over the in-phase and out-phase windows that pair with the echo time images acquired.
  • a characteristic deviation can then be determined, again in a number of ways, with a preferred method being the absolute value of the greatest deviation in a given window, which hereinafter will be referred to as the “in-phase deviation” for the in-phase window, and “out-phase deviation” for the out-phase window.
  • An initial estimate of the percentage fat fraction can be determined from the in-phase and out-phase deviations by, for example, a combination of scaling and thresholding.
  • the percentage fat fraction can be taken to be equal to the scaled out-phase deviation within empirically determined thresholds for the in-phase and out-phase deviations. Outside of these thresholds, the percentage fat fraction is no longer approximated by the scaled out-phase deviation, but is rather set to a scaling of one minus the scaled out-phase deviation.
  • One approach is to determine thresholds above which for the out-phase deviation and simultaneously below which for the in-phase deviation, the “outside of threshold” percentage fat approximation is preferred as a truer approximation of the actual percentage fat fraction than the “within threshold” percentage fat approximation.
  • initial estimates of the fat and water signal intensities at an echo time of 0 ms can be determined relative to the signal intensity at an echo time of 0 ms for the reference relaxation process.
  • the initial estimates for the relaxation rates of water and fat can also both be set relative to the relaxation rate of the reference relaxation process. These can be set as both being equal to the reference relaxation rate if the water/fat signal model is expressed as having a common relaxation rate for both water and fat.
  • the water/fat signal model is expressed as having a different relaxation rate for water and fat
  • further empirical assumptions can be made to set different initial values for the relaxation rates of water and fat, such as fat having an inherently faster relaxation than water.
  • Refinements can also be made to the initial estimates for the water/fat signal model with different relaxation rates for water and fat, by first fitting a water/fat signal model with a common relaxation rate for water and fat to the magnitude image data. The fitted values can then be used as initial estimates for the water/fat signal model with different relaxation rates for water and fat, again applying an empirical criterion that the relaxation rate of fat is faster than that for water.
  • FIG. 6 a shows an image of phantoms containing fat and imaged utilizing an embodiment of the present invention.
  • FIG. 6 b shows a graph of Region Average % fat to Actual fat % with the % fat realized from the phantoms on to the expected 1-to-1 line.

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